f4feea6b87
在 `ticker_24h_stream.py` 和 `book_ticker_stream.py` 中引入新的内存管理机制，限制进程内缓存的最大条数为 500，避免内存无限增长。更新 Redis 写入逻辑，确保在有 Redis 时优先写入 Redis，而不在进程内存中常驻数据。通过定期从 Redis 拉取数据并合并，提升了系统的内存使用效率与稳定性，同时优化了日志记录以减少高负载时的输出频率。此改动进一步增强了系统性能与资源管理能力。
239 lines
9.2 KiB
Python
239 lines
9.2 KiB
Python
"""
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最优挂单 WebSocket 流：订阅 !bookTicker，维护全市场最优买/卖价缓存。
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用于滑点估算、入场价格优化，提升交易执行效果。
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支持多进程共用：Leader 写 Redis，所有进程通过 refresh_book_ticker_from_redis_loop 从 Redis 更新本地缓存。
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文档：更新速度 5s，推送所有交易对的最优挂单（最高买单、最低卖单）。
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"""
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import asyncio
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import json
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import logging
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import time
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from typing import Dict, Optional, Any
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logger = logging.getLogger(__name__)
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try:
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from .market_ws_leader import KEY_BOOK_TICKER
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except ImportError:
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KEY_BOOK_TICKER = "market:book_ticker"
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# 最优挂单缓存：symbol -> { bidPrice, bidQty, askPrice, askQty, time }
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# 有 Redis 时由 refresh 循环从 Redis 回填，不在此无限累积
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_book_ticker_cache: Dict[str, Dict[str, Any]] = {}
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_book_ticker_updated_at: float = 0.0
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_BOOK_TICKER_CACHE_MAX_KEYS = 500 # 进程内存最多保留 500 个
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def get_book_ticker_cache() -> Dict[str, Dict[str, Any]]:
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"""返回当前最优挂单缓存。"""
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return dict(_book_ticker_cache)
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def get_book_ticker(symbol: str) -> Optional[Dict[str, Any]]:
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"""获取指定交易对的最优挂单；无缓存时返回 None。"""
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return _book_ticker_cache.get(symbol.upper())
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def is_book_ticker_cache_fresh(max_age_sec: float = 10.0) -> bool:
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"""缓存是否在 max_age_sec 秒内更新过且非空。"""
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if not _book_ticker_cache:
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return False
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return (time.monotonic() - _book_ticker_updated_at) <= max_age_sec
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def estimate_slippage(symbol: str, side: str, quantity: float) -> Optional[float]:
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"""
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估算滑点（USDT）：基于最优挂单估算执行价格与标记价格的偏差。
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Args:
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symbol: 交易对
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side: BUY/SELL
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quantity: 下单数量
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Returns:
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估算滑点（USDT），None 表示无法估算
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"""
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ticker = get_book_ticker(symbol)
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if not ticker:
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return None
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try:
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bid_price = float(ticker.get("bidPrice", 0))
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ask_price = float(ticker.get("askPrice", 0))
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bid_qty = float(ticker.get("bidQty", 0))
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ask_qty = float(ticker.get("askQty", 0))
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if bid_price <= 0 or ask_price <= 0:
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return None
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mid_price = (bid_price + ask_price) / 2
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if side == "BUY":
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# 买单：用 askPrice（卖一）估算，滑点 = (askPrice - midPrice) * quantity
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if ask_qty >= quantity:
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slippage = (ask_price - mid_price) * quantity
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else:
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# 数量超过卖一，需要吃多档，粗略估算
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slippage = (ask_price - mid_price) * quantity * 1.2
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else: # SELL
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# 卖单：用 bidPrice（买一）估算，滑点 = (midPrice - bidPrice) * quantity
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if bid_qty >= quantity:
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slippage = (mid_price - bid_price) * quantity
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else:
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slippage = (mid_price - bid_price) * quantity * 1.2
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return slippage
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except Exception:
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return None
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class BookTickerStream:
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"""订阅合约 !bookTicker，持续更新 _book_ticker_cache。Leader 时可选写 Redis 供多进程读。"""
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def __init__(self, testnet: bool = False, redis_cache: Any = None):
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self.testnet = testnet
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self._redis_cache = redis_cache
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self._ws = None
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self._task: Optional[asyncio.Task] = None
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self._running = False
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def _ws_url(self) -> str:
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if self.testnet:
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return "wss://stream.binancefuture.com/ws/!bookTicker"
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return "wss://fstream.binance.com/ws/!bookTicker"
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async def start(self) -> bool:
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if self._running:
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return True
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self._running = True
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self._task = asyncio.create_task(self._run_ws())
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logger.info("BookTickerStream: 已启动（!bookTicker），用于滑点估算")
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return True
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async def stop(self):
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self._running = False
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if self._task:
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self._task.cancel()
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try:
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await self._task
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except asyncio.CancelledError:
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pass
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self._task = None
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if self._ws:
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try:
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await self._ws.close()
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except Exception:
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pass
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self._ws = None
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logger.info("BookTickerStream: 已停止")
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async def _run_ws(self):
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import aiohttp
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while self._running:
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url = self._ws_url()
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try:
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async with aiohttp.ClientSession() as session:
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async with session.ws_connect(
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url, heartbeat=50, timeout=aiohttp.ClientTimeout(total=15)
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) as ws:
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self._ws = ws
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logger.info("BookTickerStream: WS 已连接")
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async for msg in ws:
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if not self._running:
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break
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if msg.type == aiohttp.WSMsgType.TEXT:
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self._handle_message(msg.data)
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elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSE):
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break
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except asyncio.CancelledError:
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break
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except Exception as e:
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err_msg = getattr(e, "message", str(e)) or repr(e)
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err_type = type(e).__name__
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logger.warning(
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"BookTickerStream: WS 异常 %s: %s，10s 后重连",
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err_type, err_msg,
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exc_info=logger.isEnabledFor(logging.DEBUG),
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)
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await asyncio.sleep(10)
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self._ws = None
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if not self._running:
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break
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def _handle_message(self, raw: str):
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global _book_ticker_cache, _book_ticker_updated_at
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try:
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data = json.loads(raw)
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except Exception:
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return
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if isinstance(data, dict) and "stream" in data:
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ticker_data = data.get("data", {})
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else:
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ticker_data = data
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if not isinstance(ticker_data, dict) or ticker_data.get("e") != "bookTicker":
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return
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s = (ticker_data.get("s") or "").strip().upper()
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if not s or not s.endswith("USDT"):
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return
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try:
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item = {
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"symbol": s,
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"bidPrice": float(ticker_data.get("b", 0)),
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"bidQty": float(ticker_data.get("B", 0)),
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"askPrice": float(ticker_data.get("a", 0)),
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"askQty": float(ticker_data.get("A", 0)),
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"time": int(ticker_data.get("T", 0)),
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}
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except (TypeError, ValueError):
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return
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# 有 Redis 时只写 Redis，不写进程内存（由 refresh 循环回填）
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if self._redis_cache:
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try:
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asyncio.get_event_loop().create_task(
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self._merge_and_write_book_ticker_to_redis(s, item)
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)
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except Exception as e:
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logger.debug("BookTickerStream: 写入 Redis 调度失败 %s", e)
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return
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_book_ticker_cache[s] = item
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_book_ticker_updated_at = time.monotonic()
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if len(_book_ticker_cache) > _BOOK_TICKER_CACHE_MAX_KEYS:
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keys = list(_book_ticker_cache.keys())
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for k in keys[_BOOK_TICKER_CACHE_MAX_KEYS:]:
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del _book_ticker_cache[k]
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logger.debug(f"BookTickerStream: 已更新 {s} bid={item['bidPrice']:.4f} ask={item['askPrice']:.4f}")
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async def _merge_and_write_book_ticker_to_redis(self, symbol: str, item: Dict[str, Any]) -> None:
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"""从 Redis 读出、合并单条、写回，不占用进程内存常驻"""
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try:
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if not self._redis_cache:
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return
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existing = await self._redis_cache.get(KEY_BOOK_TICKER)
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merged = dict(existing) if isinstance(existing, dict) else {}
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merged[symbol] = item
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await self._redis_cache.set(KEY_BOOK_TICKER, merged, ttl=30)
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except Exception as e:
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logger.debug("BookTickerStream: 写入 Redis 失败 %s", e)
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async def refresh_book_ticker_from_redis_loop(redis_cache: Any, interval_sec: float = 2.0) -> None:
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"""定期从 Redis 拉取 bookTicker 到本地缓存（Leader 与非 Leader 都跑），并限制条数。"""
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global _book_ticker_cache, _book_ticker_updated_at
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if redis_cache is None:
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return
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while True:
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try:
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await asyncio.sleep(interval_sec)
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data = await redis_cache.get(KEY_BOOK_TICKER)
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if data and isinstance(data, dict):
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_book_ticker_cache.update(data)
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if len(_book_ticker_cache) > _BOOK_TICKER_CACHE_MAX_KEYS:
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keys = list(_book_ticker_cache.keys())
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for k in keys[_BOOK_TICKER_CACHE_MAX_KEYS:]:
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del _book_ticker_cache[k]
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_book_ticker_updated_at = time.monotonic()
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logger.debug("BookTicker: 从 Redis 刷新 %s 个交易对", len(_book_ticker_cache))
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except asyncio.CancelledError:
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break
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except Exception as e:
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logger.debug("BookTicker: 从 Redis 刷新失败 %s", e)
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